Engenheiro(a) de Dados Pleno
This position is posted by Jobgether on behalf of a partner company. We are currently looking for an Engenheiro(a) de Dados Pleno in Brazil.
This role is focused on building and evolving modern data solutions in a highly scalable, cloud-native environment for a major client in the financial sector. You will work across the full data lifecycle, from ingestion to final data consumption, ensuring reliable, high-performance pipelines that support critical business decisions. Operating within an Azure-based Lakehouse architecture, you will transform complex business requirements into robust data assets using Databricks and dbt. The environment is highly technical and dynamic, requiring strong engineering discipline and attention to data quality, governance, and performance. You will collaborate closely with cross-functional teams to deliver end-to-end solutions that are both scalable and production-ready. It is a hands-on role ideal for professionals who thrive in data-intensive, fast-paced environments.
Accountabilities:
- Design, build, and maintain scalable data pipelines using Python, SQL, and PySpark, ensuring efficient processing of large-scale datasets
- Develop and manage data transformations using dbt, applying business rules and ensuring quality, documentation, and testability
- Structure and maintain data within a Lakehouse architecture using the Medallion model (Bronze, Silver, Gold layers)
- Implement and support data governance practices, including access control, lineage, and catalog management via Unity Catalog
- Ensure reliability and performance of data storage and processing using Delta Lake
- Contribute to DevOps practices, including Git versioning and CI/CD pipelines (Azure DevOps), ensuring secure and traceable deployments
- Collaborate with cross-functional teams to support data initiatives and promote engineering best practices
- Translate business requirements into robust, scalable, and maintainable data solutions
- Strong experience with Python, SQL, PySpark, and especially dbt for data transformation workflows
- Hands-on experience with Databricks, Delta Lake, and Unity Catalog
- Solid knowledge of Azure cloud infrastructure and data engineering services
- Experience with Git and CI/CD processes, preferably using Azure DevOps
- Strong understanding of Lakehouse architecture and Medallion design pattern
- Ability to build and optimize scalable data pipelines in high-volume environments
- Strong analytical thinking and problem-solving skills
- Good communication skills and ability to work collaboratively in technical teams
- Nice to have: experience in financial services environments
- Nice to have: knowledge of data privacy regulations such as LGPD and GDPR
- 100% remote work model (anywhere office)
- Performance evaluation and individual development plan
- Career growth and learning program (“Investindo em Você”)
- Health and dental insurance plan
- Wellness and mental health support program
- Birthday day off
- Home office/equipment assistance
- Flexible benefits allowance for daily expenses
- Employee referral bonus program
- Life insurance coverage
- Gamified challenges with reward store system.
Requirements:
Benefits:
How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1